Contribuições da Campanha Presidencial America em 2016, estado do TX por Daniel Teobaldo
Introdução
Para este projeto escolhi uma das bases de dados sugeridas pela Udacity: Financiamento da Campanha Presidencial dos EUA de 2016.
A idéia inicial era de se fazer a analise do estado de NY, no entanto havia uma discrepancia muito grande nas contibuições uma vez que o comite “HILLARY VICTORY FUND” foi responsável por 45% do valor financiado referente a este estado em apenas 23 das 649.460 contribuições registradas, sendo todas elas com valores acima de U$ 100.000. Este foi o único contribuinte que realizou contribuições acima deste valor. A maior contribuição abaixo deste valor de U$ 100.000 foi de U$ 11.816,25. Poderia ser feita uma remoção dos outliers, porém esta ação traria um dataset que não representa o conjunto de dados do estado.
#Verifica a distribuição dos valores de controbuições do dataset
summary(USACampaign$contb_receipt_amt)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -10100 15 27 264 100 12777706USACampaign$contb_receipt_amt <- abs(USACampaign$contb_receipt_amt)
USACampaign$contb_range <- cut(USACampaign$contb_receipt_amt, c(0,100,500,2000,50000,max(USACampaign$contb_receipt_amt)))
#Verifica contribuintes com contribuições superiores a U$ 100.000
USACampaign[USACampaign$contb_receipt_amt >= 100000,]$contbr_nm## [1] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [3] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [5] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [7] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [9] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [11] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [13] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [15] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [17] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [19] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [21] HILLARY VICTORY FUND - UNITEMIZED HILLARY VICTORY FUND - UNITEMIZED
## [23] HILLARY VICTORY FUND - UNITEMIZED
## 119407 Levels: BLACKMORE, ANDI POTAMKIN ... ZYWICZYNSKI, JERRY MR.#Valor máximo abaixo de U$ 100.000
max(USACampaign[USACampaign$contb_receipt_amt < 100000,]$contb_receipt_amt)## [1] 11816.25sum(USACampaign[USACampaign$contbr_nm == "HILLARY VICTORY FUND - UNITEMIZED",]$contb_receipt_amt)/sum(USACampaign$contb_receipt_amt)*100## [1] 45.12158dim(USACampaign[USACampaign$contbr_nm == "HILLARY VICTORY FUND - UNITEMIZED",])## [1] 23 21USACampaign$hillary_comitte <- ifelse(USACampaign$contbr_nm == "HILLARY VICTORY FUND - UNITEMIZED", "Y", "N")Quando comparamos as contribuições do contribuinte HILLARY VICTORY FUND - UNITEMIZED e os demais contribuintes, vemos que o valor total das contribuições são próximos, porém as quantidade de contribuições da comite da Hillary são significamente menores.
Abaixo uma comparação entre a quantidade de contribuições realizadas por faixa de valor versus o total arrecadado.
É possível notar também o impacto das contribuições de valores elevados quando comparamos os quartils dos valores com e sem estas contribuições, para cada candidato.
Esta discrepancia prejudicaria a avaliação das contribuições entre os candidatos e restringiria as analises dos dados. Desta forma optei por fazer a analise das contribuições feitas pelos eleitores do estado do TX, que traz uma distribuição mais homogenea nas contribuições.
=============================================================
Analise do dataset do estado do Texas
## [1] 12084 19## [1] 24 19##
## DALLA DALLAA DALLAD DALLALS DALLAS
## 1 1 4 1 40656
## DALLAS TEXAS DALLAS TX DALLAS, DALLAS, TX DALLAS9
## 2 1 1 1 1
## DALLASTX DALLASV DALLLAS
## 1 2 1Algumas verificações simples nesta base de dados nos aponta necessidade de tratamento das informações. Este tratamento será feito em um script a parte, em python (tratarDados.py). Maiores detalhes sobre este tratamentos pode ser visualizado no arquivo Tratamento de dados.md.
## [1] 16600## RETIRED NOT EMPLOYED
## 142978 29745 24405
## LAWYER SELF-EMPLOYED TEACHER
## 17517 13267 13119
## HOMEMAKER ENGINEER PHYSICIAN
## 11325 9016 8817
## SALES NURSE CONSULTANT
## 6943 5613 5519
## REAL ESTATE MANAGER ACCOUNTANT
## 5327 4851 4054
## SOFTWARE DEVELOPER CEO PRESIDENT
## 2896 2750 2386
## SOFTWARE ENGINEER RN STUDENT
## 2374 2372 2357
## CPA EXECUTIVE EDUCATOR
## 2081 2008 1866
## PROJECT MANAGER DIRECTOR WRITER
## 1710 1472 1425
## RANCHER TRUCK DRIVER MARKETING
## 1409 1403 1279
## OFFICE MANAGER INSURANCE PILOT
## 1262 1224 1167
## PHARMACIST ARTIST ADMINISTRATOR
## 1118 1096 1049
## PSYCHOLOGIST ANALYST GEOLOGIST
## 1049 1034 1030
## INVESTOR CONSTRUCTION FARMER
## 1021 1005 977
## CONTRACTOR LIBRARIAN PARALEGAL
## 970 966 945
## REFUSED CFO SOCIAL WORKER
## 922 901 880
## VICE PRESIDENT ARCHITECT DENTIST
## 859 857 843
## MANAGEMENT DISABLED IT
## 806 805 777
## FINANCE DRIVER BOOKKEEPER
## 754 739 720
## PASTOR MUSICIAN INVESTMENTS
## 716 715 704
## ELECTRICIAN BANKER SALES MANAGER
## 665 659 659
## IT MANAGER FINANCIAL ADVISOR DESIGNER
## 652 641 640
## MINISTER VETERINARIAN PHOTOGRAPHER
## 616 615 605
## GENERAL MANAGER PSYCHOTHERAPIST FLIGHT ATTENDANT
## 573 573 572
## GEOPHYSICIST GRAPHIC DESIGNER SECRETARY
## 572 569 567
## SCIENTIST TECHNICIAN ENTREPRENEUR
## 564 534 523
## PROPERTY MANAGER BUSINESS ANALYST SUPERVISOR
## 514 513 499
## RETAIL EDUCATION CLERK
## 484 480 477
## ADMINISTRATIVE ASSISTANT LEGAL ASSISTANT BUSINESS
## 471 470 469
## PHYSICAL THERAPIST ELECTRICAL ENGINEER HUMAN RESOURCES
## 468 456 456
## LANDMAN BANKING SOFTWARE
## 454 449 447
## EXECUTIVE DIRECTOR EXECUTIVE ASSISTANT ACCOUNT MANAGER
## 440 437 429
## SALES REPRESENTATIVE PARTNER (Other)
## 418 403 168005
## NA's
## 139## Min. 1st Qu. Median Mean 3rd Qu.
## "2013-10-21" "2016-02-06" "2016-04-29" "2016-04-27" "2016-08-12"
## Max.
## "2016-12-31"## [1] 548372 29## [1] "cmte_id" "cand_id"
## [3] "cand_nm" "contbr_nm"
## [5] "contbr_city" "contbr_st"
## [7] "contbr_zip" "contbr_employer"
## [9] "contbr_occupation" "contb_receipt_amt"
## [11] "contb_receipt_dt" "receipt_desc"
## [13] "memo_cd" "memo_text"
## [15] "form_tp" "file_num"
## [17] "tran_id" "election_tp"
## [19] "X" "city"
## [21] "lon" "lat"
## [23] "party" "cmte_nm"
## [25] "cmte_dsgn" "contb_receipt_dt_day"
## [27] "contb_receipt_dt_month" "contb_receipt_dt_year"
## [29] "contb_receipt_date"## 'data.frame': 548372 obs. of 29 variables:
## $ cmte_id : Factor w/ 26 levels "C00458844","C00496034",..: 7 16 16 8 7 7 16 16 7 16 ...
## $ cand_id : Factor w/ 25 levels "P00003392","P20002671",..: 1 23 23 12 1 1 23 23 1 23 ...
## $ cand_nm : Factor w/ 25 levels "Bush, Jeb","Carson, Benjamin S.",..: 4 23 23 20 4 4 23 23 4 23 ...
## $ contbr_nm : chr "MILLARD, SUSAN C." "SELLERS, CHRISTINE" "SELLERS, DAVID" "LEONE, MICHELLE" ...
## $ contbr_city : chr "CORPUS CHRISTI" "FORT WORTH" "WILLIS" "NORTH RICHLAND HILLS" ...
## $ contbr_st : chr "TX" "TX" "TX" "TX" ...
## $ contbr_zip : chr "784112213" "76108" "77318" "761826749" ...
## $ contbr_employer : chr "N/A" "BAYLOR HEALTHCARE SYSTEM" "RETIRED" "NOT EMPLOYED" ...
## $ contbr_occupation : Factor w/ 17309 levels ""," COUNSELOR",..: 13427 10139 13427 10106 14283 13859 1 1 11331 7205 ...
## $ contb_receipt_amt : num 37.1 127.1 80 15 50 ...
## $ contb_receipt_dt : chr "16-APR-16" "28-SEP-16" "01-DEC-16" "06-MAR-16" ...
## $ receipt_desc : chr "" "" "" "" ...
## $ memo_cd : logi NA NA NA NA NA NA ...
## $ memo_text : logi NA NA NA NA NA NA ...
## $ form_tp : chr "SA18" "SA18" "SA18" "SA17A" ...
## $ file_num : int 1091718 1146165 1146165 1077404 1091718 1091718 1146165 1146165 1091718 1146165 ...
## $ tran_id : chr "C4725643" "SA18.90357" "SA18.120784" "VPF7BKZGYE4" ...
## $ election_tp : chr "P2016" "G2016" "G2016" "P2016" ...
## $ X : logi NA NA NA NA NA NA ...
## $ city : chr "CORPUS CHRISTI" "FORT WORTH" "WILLIS" "NORTH RICHLAND HILLS" ...
## $ lon : num -97.4 -97.3 -95.5 -97.2 -98.5 ...
## $ lat : num 27.8 32.8 30.4 32.9 29.4 ...
## $ party : chr "DEM" "REP" "REP" "DEM" ...
## $ cmte_nm : chr "HILLARY FOR AMERICA" "DONALD J. TRUMP FOR PRESIDENT, INC." "DONALD J. TRUMP FOR PRESIDENT, INC." "BERNIE 2016" ...
## $ cmte_dsgn : chr "P" "P" "P" "P" ...
## $ contb_receipt_dt_day : int 16 28 1 6 9 4 29 30 21 4 ...
## $ contb_receipt_dt_month: Ord.factor w/ 12 levels "JAN"<"FEB"<"MAR"<..: 4 9 12 3 4 4 11 11 4 10 ...
## $ contb_receipt_dt_year : int 16 16 16 16 16 16 16 16 16 16 ...
## $ contb_receipt_date : Date, format: "2016-04-16" "2016-09-28" ...## cmte_id cand_id cand_nm
## C00575795:203928 P00003392:203928 Clinton, Hillary Rodham :203928
## C00574624:138799 P60006111:138799 Cruz, Rafael Edward 'Ted':138799
## C00577130: 79955 P60007168: 79955 Sanders, Bernard : 79955
## C00580100: 77916 P80001571: 77916 Trump, Donald J. : 77916
## C00573519: 23694 P60005915: 23694 Carson, Benjamin S. : 23694
## C00458844: 8984 P60006723: 8984 Rubio, Marco : 8984
## (Other) : 15096 (Other) : 15096 (Other) : 15096
## contbr_nm contbr_city contbr_st
## Length:548372 Length:548372 Length:548372
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## contbr_zip contbr_employer contbr_occupation
## Length:548372 Length:548372 RETIRED :142978
## Class :character Class :character : 29745
## Mode :character Mode :character NOT EMPLOYED : 24405
## LAWYER : 17517
## SELF-EMPLOYED: 13267
## (Other) :320321
## NA's : 139
## contb_receipt_amt contb_receipt_dt receipt_desc memo_cd
## Min. : 0.01 Length:548372 Length:548372 Mode:logical
## 1st Qu.: 25.00 Class :character Class :character NA's:548372
## Median : 40.00 Mode :character Mode :character
## Mean : 175.02
## 3rd Qu.: 100.00
## Max. :16600.00
##
## memo_text form_tp file_num tran_id
## Mode:logical Length:548372 Min. :1003942 Length:548372
## NA's:548372 Class :character 1st Qu.:1077404 Class :character
## Mode :character Median :1096256 Mode :character
## Mean :1097493
## 3rd Qu.:1133832
## Max. :1146285
##
## election_tp X city lon
## Length:548372 Mode:logical Length:548372 Min. :-124.03
## Class :character NA's:548372 Class :character 1st Qu.: -97.74
## Mode :character Mode :character Median : -96.93
## Mean : -97.11
## 3rd Qu.: -95.47
## Max. : -71.06
## NA's :613
## lat party cmte_nm cmte_dsgn
## Min. :24.66 Length:548372 Length:548372 Length:548372
## 1st Qu.:29.76 Class :character Class :character Class :character
## Median :30.26 Mode :character Mode :character Mode :character
## Mean :30.99
## 3rd Qu.:32.76
## Max. :46.88
## NA's :613
## contb_receipt_dt_day contb_receipt_dt_month contb_receipt_dt_year
## Min. : 1.00 OCT : 68919 Min. :13.00
## 1st Qu.: 8.00 JUL : 57731 1st Qu.:16.00
## Median :16.00 MAR : 56585 Median :16.00
## Mean :16.36 SEP : 52846 Mean :15.81
## 3rd Qu.:25.00 APR : 50181 3rd Qu.:16.00
## Max. :31.00 AUG : 49822 Max. :16.00
## (Other):212288
## contb_receipt_date
## Min. :2013-10-21
## 1st Qu.:2016-02-06
## Median :2016-04-29
## Mean :2016-04-27
## 3rd Qu.:2016-08-12
## Max. :2016-12-31
## Este dataset do estado do Texas contem 548.396 observações com 28 variaveis. O dataset original (sem tratamento) contém 18 variáveis.
Seção de Gráficos Univariados
Uma analise importante é como as contribuições estão distribuidas por candidato. Já pensando em uma analise por partido, neste gráfico já decidi classificar os candidatos. Para a difinição do partido, consideramos a classificação registrada na base de dados de candidatos obtida no site da FEC.
Nesta análise percebemos que a grande maioria das contribuições se concentram nos 4 primeiros candidatos, mas é importante notar que quando ordenamos por valor total arrecadado, existe um inversão nas posições. Devido a essa inversão farei uma análise focada nos 7 candidatos com maior volume arrecada, no lugar de 5 candidatos que era a idéia inicial.
Uma analise mais detalhada desse aspecto será realizada na seção de gráficos bivariados.
Como esperado, nota-se que a maior parte das contribuições se destinam aos candidatos democratas (DEM) e republicanos (REP), desta forma vamos considerar apenas estes 2 partidos nas analises.
Nesta analise procurei fazer uma avaliação identificardas contribuições ocorreram ao longo do período. Primeiro considerei todo o período do dataset e então fiz uma analise focada em 2016, ano da eleição.
## Min. 1st Qu. Median Mean 3rd Qu.
## "2013-10-21" "2016-02-06" "2016-04-29" "2016-04-27" "2016-08-12"
## Max.
## "2016-12-31"
Em uma análise da distribuição dos valores de contribuições já podemos perceber como as contribuições de menores valores são a maioria em quantidade, como já se era de esperar.
Para uma analise de um espectro maior de valores, reduzi o binwidth em 10x. Na sequência apliqei uma escala logaritima para exibir melhor o valores com menos contribuuções e reduzi o limite do eixo x com o objetivo de focar nos valores de contribuições mais frequentes, chegando no limite de um quartil de 95%.
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.01 25.00 40.00 175.02 100.00 16600.00
## 95%
## 700
Decidi classificar os valores de contribuição considerando as seguintes faixas de valores: - Até 100,00 - 100,01 a 500,00 - 500,01 a 2.000,00 - Acima de 2.000,00
## # A tibble: 30 x 2
## city count
## <chr> <int>
## 1 HOUSTON 71294
## 2 AUSTIN 57745
## 3 DALLAS 41118
## 4 SAN ANTONIO 30240
## 5 FORT WORTH 16307
## 6 SPRING 12167
## 7 PLANO 9603
## 8 EL PASO 7763
## 9 ARLINGTON 7324
## 10 KATY 6063
## # ... with 20 more rows
## # A tibble: 10 x 2
## contbr_occupation count
## <fctr> <int>
## 1 RETIRED 142978
## 2 29745
## 3 NOT EMPLOYED 24405
## 4 LAWYER 17517
## 5 SELF-EMPLOYED 13267
## 6 TEACHER 13119
## 7 HOMEMAKER 11325
## 8 ENGINEER 9016
## 9 PHYSICIAN 8817
## 10 SALES 6943
Análise Univariada
Qual é a estrutura do conjunto de dados?
O conjunto de dados possui registros de contribuições para o estado de TX, com 28 atributos no arquivo tratado e 18 no arquivo original.
Quais são os principais atributos de interesse deste conjunto de dados?
Os principais atributos deste conjunto de dados são os candidatos (cand_nm) e os valores das contribuições (contb_receipt_amt).
Quais outros atributos você acha que podem lhe auxiliar na investigação destes atributos de interesse?
Atributos realcionados a origem das contribuições serão muito úteis nesta analise. Entre elas estão:
- Nome do comite
- Nome do contribuinte
- Data de contribuição
- Ocupação do contribuinte
- Cidade do contribuinte
Além destas existem variáveis importantes como o partido do candidato.
Você criou novas variáveis a partir dos atributos existentes no conjunto de dados?
Sim. Foram criados as seguintes variaveis: - A partir da data, criei colunas com os componentes da data de contribuição (dia, mês e ano) - Foram incorporados dados do dataset de CEP (zipcode): cidade, longitude e latitude - Foi adicionada uma coluna com faixas dos valores doados. - A partir da base de dados dos candidatos (obtido na FEC), foi incorporado o partido do candidato - A partir da base de dados dos comites (obtido na FEC), foi incorporado o nome do comite
Dos atributos investigados, distribuições incomuns foram encontradas? Você aplicou operações nos dados para limpá-los, ajustá-los ou mudar a forma dos dados? Se sim, por quê?
Foram realizados tratamentos nos valores de contribuição. Para os valores negativos, foi considerado o valor absoluto. As contribuições zeradas foram eliminadas.
As datas de contribuição carregadas originalmente como caracter, foram convertidas para Date e quebrada em colunas separadas para dia, mes e ano.
Conforme apresentado na seção de tratamento de dados, fiz uma ajuste nos nomes das cidades para eleminar as cidades iguais registradas com grafias diferentes. O mesmo tratamento foi realizado para a ocupação dos contribuintes.
Todos os tratamentos foram realizados num script python a parte (tratarDados.py).
Seção de Gráficos Bivariados
Aqui fiz uma analise das distriuição dos valores ao longo do tempo. No primeiro gráfico foi feita uma analise mais ampla por todo o período compreendido no dataset. No segundo reduzi o faixa de valores para o ano de 2016 e foi considerada as contribuições realizadas dentro de 99% da amostragem.
## `geom_smooth()` using method = 'gam'
## `geom_smooth()` using method = 'gam'## Warning: Removed 101744 rows containing non-finite values (stat_smooth).## Warning: Removed 104466 rows containing missing values (geom_point).
Nesta analise podemos perceber a presença de faixas horizontais bem definidas para os valores doados com mais frequncias. Estes normalmente ão valores redodndos. Uma faixa bem definida é a 2700 dolares, que era o limite máximo permitido para pessoas físicas Limites de contribuições - FEC. Considerando eleições primárias e geral, é possível uma doação de $5.400,00 (2.700 para cada).
Estas mesmas faixas podem ser percebidas quando analisamos a os valores de contribuição por candidato, como visto abaixo.
## Warning: Removed 7214 rows containing missing values (geom_point).
Nesta sequencia de gráficos vemos as relações entre candidatos e valores de contribuição. Ao contrário do que normalmente seria esperado, o candidato com mais contribuições não é o mesmo com maior valor arrecadado. O candidato Jeb Bush, apesar de possuir menos de 5% das contribuições de Bernard Sanders, conseguiu arrecadar um pouco que o este. No caso especial de Jeb Bush, isto pode ter relação com o fato do Texas ser o seu estado Natal, além da sua relação com os outros 2 ex-presidentes Bush (pai e irmão).
## # A tibble: 7 x 4
## cand_nm qtde valor_total valor_medio
## <fctr> <int> <dbl> <dbl>
## 1 Bush, Jeb 3578 4523399.1 1264.2256
## 2 Carson, Benjamin S. 23694 3830272.6 161.6558
## 3 Christie, Christopher J. 198 295205.0 1490.9343
## 4 Clinton, Hillary Rodham 203928 23341676.1 114.4604
## 5 Cruz, Rafael Edward 'Ted' 138799 33971577.3 244.7538
## 6 Fiorina, Carly 2541 682558.6 268.6181
## 7 Gilmore, James S III 5 11800.0 2360.0000
Um comportamento semelhante pode ser observado quando analisamos os 2 principais partidos (Democratas e Republicanos). Embora os democratas tenham uma quantidade de contribuições maior do que a dos republicanos (feitas principalmente em nome de Hillary Cinton), o valor arreacadado do segundo é quase o dobro do primeiro.
Na distribuição das doações entre as cidades do estado do TX, temos Austin em segundo, atrás apenas da cidade de Houston, porém quando analisamos o valor total, Dallas vem em segundo, deixando Austin em terceiro. Isto poderia estar relacionada a renda media de cada cidade mas sem os dados de rendimentos não é possível esta analise.
Por fim fiz uma analise da distribuição geográfica das doações com base nas informações de longitude (lon) e latitude (lat) recolhidas na base de dados de zipcode.
Como esperado, a maioria das doação estão concentradas na parte leste do estado, onde se localizam as cidades com maior quantidade de contribuições: Houston, Austin e Dallas.
## Warning: use rgdal::readOGR or sf::st_read
## Warning: use rgdal::readOGR or sf::st_read## Object of class SpatialPolygonsDataFrame
## Coordinates:
## min max
## x -106.64565 -93.50804
## y 25.83716 36.50070
## Is projected: NA
## proj4string : [NA]
## Data attributes:
## STATEFP COUNTYFP COUSUBFP COUSUBNS GEOID
## 48:862 027 : 9 90005 : 1 01938476: 1 4800190650: 1
## 309 : 9 90010 : 1 01938477: 1 4800191205: 1
## 085 : 8 90015 : 1 01938478: 1 4800191390: 1
## 099 : 8 90017 : 1 01938479: 1 4800192615: 1
## 215 : 8 90020 : 1 01938480: 1 4800192945: 1
## 277 : 8 90025 : 1 01938481: 1 4800390085: 1
## (Other):812 (Other):856 (Other) :856 (Other) :856
## NAME NAMELSAD LSAD CLASSFP
## Cedar Creek Lake: 3 Cedar Creek Lake CCD: 3 22:862 Z5:862
## Amarillo : 2 Amarillo CCD : 2
## Dalhart : 2 Dalhart CCD : 2
## Fort Hood : 2 Fort Hood CCD : 2
## Gladewater : 2 Gladewater CCD : 2
## Kilgore : 2 Kilgore CCD : 2
## (Other) :849 (Other) :849
## MTFCC CNECTAFP NECTAFP NCTADVFP FUNCSTAT ALAND
## G4040:862 NA's:862 NA's:862 NA's:862 S:862 Min. :2.939e+07
## 1st Qu.:3.446e+08
## Median :5.289e+08
## Mean :7.850e+08
## 3rd Qu.:9.027e+08
## Max. :9.519e+09
##
## AWATER INTPTLAT INTPTLON
## Min. :0.000e+00 +25.9648763: 1 -093.7054610: 1
## 1st Qu.:1.255e+06 +26.1029227: 1 -093.7135949: 1
## Median :3.961e+06 +26.1388555: 1 -093.7757556: 1
## Mean :2.206e+07 +26.1503878: 1 -093.7858765: 1
## 3rd Qu.:1.177e+07 +26.1710987: 1 -093.7971206: 1
## Max. :1.262e+09 +26.1883773: 1 -093.8170037: 1
## (Other) :856 (Other) :856## STATEFP COUNTYFP COUSUBFP COUSUBNS GEOID
## 0 48 133 91590 01938795 4813391590
## 1 48 133 93190 01939119 4813393190
## 2 48 133 91135 01938705 4813391135
## 3 48 133 93250 01939131 4813393250
## 4 48 125 93705 01939223 4812593705
## 5 48 125 91050 01938688 4812591050
## 6 48 205 90690 01938616 4820590690
## 7 48 117 91785 01938838 4811791785
## 8 48 117 91790 01938839 4811791790
## 9 48 219 93320 01939145 4821993320
## 10 48 131 93215 01939124 4813193215
## 11 48 131 90260 01938527 4813190260
## 12 48 277 92970 01939075 4827792970
## 13 48 053 90450 01938565 4805390450
## 14 48 289 92775 01939036 4828992775
## 15 48 423 93950 01939272 4842393950
## 16 48 423 94205 01939323 4842394205
## 17 48 423 93970 01939276 4842393970
## 18 48 423 94260 01939334 4842394260
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## 511 48 437 92060 01938893 4843792060
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## 514 48 391 94275 01939337 4839194275
## 515 48 401 93148 01938601 4840193148
## 516 48 401 92925 01939066 4840192925
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## 518 48 403 91765 01938834 4840391765
## 519 48 067 90320 01938539 4806790320
## 520 48 067 92405 01938962 4806792405
## 521 48 061 91115 01938701 4806191115
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## 523 48 061 90480 01938571 4806190480
## 524 48 061 92295 01938940 4806192295
## 525 48 351 90530 01938581 4835190530
## 526 48 351 92750 01939031 4835192750
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## 530 48 281 92255 01938932 4828192255
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## 533 48 189 90005 01938476 4818990005
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## 535 48 189 93020 01939085 4818993020
## 536 48 189 93060 01939093 4818993060
## 537 48 141 91215 01938721 4814191215
## 538 48 141 91230 01938724 4814191230
## 539 48 141 91225 01938723 4814191225
## 540 48 363 91595 01938796 4836391595
## 541 48 363 92950 01939071 4836392950
## 542 48 481 90368 01939029 4848190368
## 543 48 481 94185 01939319 4848194185
## 544 48 337 92610 01939003 4833792610
## 545 48 065 92965 01939074 4806592965
## 546 48 065 94195 01939321 4806594195
## 547 48 221 91610 01938799 4822191610
## 548 48 021 90210 01938517 4802190210
## 549 48 021 93600 01939202 4802193600
## 550 48 141 91220 01938722 4814191220
## 551 48 183 92270 01938935 4818392270
## 552 48 183 92193 01939158 4818392193
## 553 48 135 94173 01938786 4813594173
## 554 48 007 93295 01939140 4800793295
## 555 48 147 93200 01939121 4814793200
## 556 48 285 92655 01939012 4828592655
## 557 48 435 93620 01939206 4843593620
## 558 48 405 90455 01938566 4840590455
## 559 48 193 91690 01938819 4819391690
## 560 48 193 91800 01938841 4819391800
## 561 48 161 91275 01938732 4816191275
## 562 48 195 91660 01938809 4819591660
## 563 48 195 93695 01939221 4819593695
## 564 48 067 90160 01938507 4806790160
## 565 48 161 90555 01938586 4816190555
## 566 48 161 93850 01939252 4816193850
## 567 48 389 92990 01939079 4838992990
## 568 48 389 90190 01938513 4838990190
## 569 48 097 91435 01938764 4809791435
## 570 48 499 90025 01938480 4849990025
## 571 48 499 91740 01938829 4849991740
## 572 48 499 94255 01939333 4849994255
## 573 48 499 93180 01939117 4849993180
## 574 48 289 90680 01938614 4828990680
## 575 48 289 92427 01938869 4828992427
## 576 48 453 92807 01939268 4845392807
## 577 48 453 92857 01939269 4845392857
## 578 48 453 90165 01938508 4845390165
## 579 48 265 91875 01938856 4826591875
## 580 48 401 91775 01938836 4840191775
## 581 48 379 93075 01939096 4837993075
## 582 48 041 90495 01938574 4804190495
## 583 48 041 93635 01939209 4804193635
## 584 48 041 92790 01939039 4804192790
## 585 48 067 92215 01938924 4806792215
## 586 48 067 91850 01938851 4806791850
## 587 48 179 92172 01939073 4817992172
## 588 48 179 92365 01938954 4817992365
## 589 48 179 92955 01939072 4817992955
## 590 48 367 94095 01939301 4836794095
## 591 48 019 90195 01938514 4801990195
## 592 48 019 92500 01938981 4801992500
## 593 48 291 90755 01938629 4829190755
## 594 48 291 92195 01938920 4829192195
## 595 48 291 90945 01938667 4829190945
## 596 48 327 92515 01938984 4832792515
## 597 48 327 92520 01938985 4832792520
## 598 48 313 92860 01939053 4831392860
## 599 48 313 92575 01938996 4831392575
## 600 48 433 90150 01938505 4843390150
## 601 48 321 92940 01939069 4832192940
## 602 48 321 90220 01938519 4832190220
## 603 48 151 92350 01938951 4815192350
## 604 48 151 93340 01939150 4815193340
## 605 48 151 93275 01939136 4815193275
## 606 48 171 91395 01938756 4817191395
## 607 48 171 93757 01938757 4817193757
## 608 48 471 93255 01939132 4847193255
## 609 48 051 90825 01938643 4805190825
## 610 48 051 92890 01939059 4805192890
## 611 48 051 93610 01939204 4805193610
## 612 48 169 93108 01939104 4816993108
## 613 48 305 92880 01939057 4830592880
## 614 48 321 93915 01939265 4832193915
## 615 48 485 91195 01938717 4848591195
## 616 48 473 91770 01938835 4847391770
## 617 48 473 93137 01939295 4847393137
## 618 48 033 91425 01938762 4803391425
## 619 48 109 94015 01939285 4810994015
## 620 48 227 90300 01938535 4822790300
## 621 48 461 92345 01938950 4846192345
## 622 48 461 93195 01939120 4846193195
## 623 48 059 90910 01938660 4805990910
## 624 48 471 92755 01939032 4847192755
## 625 48 055 92245 01938930 4805592245
## 626 48 055 92440 01938969 4805592440
## 627 48 305 94230 01939328 4830594230
## 628 48 477 90435 01938562 4847790435
## 629 48 477 94080 01939298 4847794080
## 630 48 477 90550 01938585 4847790550
## 631 48 237 91905 01938862 4823791905
## 632 48 491 93343 01938776 4849193343
## 633 48 491 90657 01938921 4849190657
## 634 48 277 90345 01938544 4827790345
## 635 48 277 93130 01939107 4827793130
## 636 48 277 90285 01938532 4827790285
## 637 48 277 93355 01939153 4827793355
## 638 48 439 91380 01938753 4843991380
## 639 48 309 90715 01938621 4830990715
## 640 48 309 92355 01938952 4830992355
## 641 48 309 94055 01939293 4830994055
## 642 48 309 90895 01938657 4830990895
## 643 48 309 91210 01938720 4830991210
## 644 48 309 94140 01939310 4830994140
## 645 48 309 92631 01939007 4830992631
## 646 48 309 90175 01938510 4830990175
## 647 48 491 91325 01938742 4849191325
## 648 48 491 93845 01939251 4849193845
## 649 48 491 91915 01938864 4849191915
## 650 48 095 91160 01938710 4809591160
## 651 48 365 90970 01938672 4836590970
## 652 48 365 90235 01938522 4836590235
## 653 48 503 91935 01938868 4850391935
## 654 48 503 92735 01939028 4850392735
## 655 48 395 91750 01938831 4839591750
## 656 48 395 90430 01938561 4839590430
## 657 48 395 91385 01938754 4839591385
## 658 48 441 90010 01938477 4844190010
## 659 48 441 91945 01938870 4844191945
## 660 48 267 91965 01938874 4826791965
## 661 48 455 91530 01938783 4845591530
## 662 48 455 90120 01938499 4845590120
## 663 48 137 93300 01939141 4813793300
## 664 48 307 92505 01938982 4830792505
## 665 48 307 93280 01939137 4830793280
## 666 48 487 91730 01938827 4848791730
## 667 48 487 92240 01938929 4848792240
## 668 48 487 94030 01939288 4848794030
## 669 48 113 92792 01939038 4811392792
## 670 48 501 93055 01939092 4850193055
## 671 48 009 90130 01938501 4800990130
## 672 48 209 93430 01939168 4820993430
## 673 48 209 91075 01938693 4820991075
## 674 48 015 90250 01938525 4801590250
## 675 48 015 94070 01939296 4801594070
## 676 48 015 93490 01939180 4801593490
## 677 48 015 91873 01939315 4801591873
## 678 48 119 92985 01939078 4811992985
## 679 48 419 90670 01938612 4841990670
## 680 48 119 90840 01938646 4811990840
## 681 48 419 93925 01939267 4841993925
## 682 48 021 90655 01938609 4802190655
## 683 48 021 91200 01938718 4802191200
## 684 48 387 90735 01938625 4838790735
## 685 48 083 93830 01939248 4808393830
## 686 48 083 92865 01939054 4808392865
## 687 48 159 94250 01939332 4815994250
## 688 48 215 91710 01938823 4821591710
## 689 48 215 92340 01938949 4821592340
## 690 48 215 93650 01939212 4821593650
## 691 48 023 93525 01939188 4802393525
## 692 48 073 90045 01938484 4807390045
## 693 48 073 92670 01939015 4807392670
## 694 48 073 92745 01939030 4807392745
## 695 48 387 90105 01938496 4838790105
## 696 48 387 92385 01938958 4838792385
## 697 48 387 91025 01938683 4838791025
## 698 48 377 93145 01939110 4837793145
## 699 48 223 92815 01939044 4822392815
## 700 48 439 90135 01938502 4843990135
## 701 48 439 92805 01939042 4843992805
## 702 48 267 91960 01938873 4826791960
## 703 48 335 92285 01938938 4833592285
## 704 48 407 93555 01939193 4840793555
## 705 48 227 90305 01938536 4822790305
## 706 48 227 90770 01938632 4822790770
## 707 48 449 93825 01939247 4844993825
## 708 48 449 94235 01939329 4844994235
## 709 48 115 92120 01938905 4811592120
## 710 48 115 92105 01938902 4811592105
## 711 48 115 92110 01938903 4811592110
## 712 48 223 90930 01938664 4822390930
## 713 48 223 93790 01939240 4822393790
## 714 48 373 90860 01938650 4837390860
## 715 48 185 90080 01938491 4818590080
## 716 48 419 93550 01939192 4841993550
## 717 48 419 93860 01939254 4841993860
## 718 48 419 90020 01938479 4841990020
## 719 48 423 90515 01938578 4842390515
## 720 48 423 92210 01938923 4842392210
## 721 48 423 93975 01939277 4842393975
## 722 48 157 92915 01939064 4815792915
## 723 48 157 93780 01939238 4815793780
## 724 48 157 92715 01939024 4815792715
## 725 48 173 91460 01938769 4817391460
## 726 48 173 91455 01938768 4817391455
## 727 48 373 92226 01938926 4837392226
## 728 48 135 92875 01939056 4813592875
## 729 48 263 91925 01938866 4826391925
## 730 48 317 93835 01939249 4831793835
## 731 48 495 94240 01939330 4849594240
## 732 48 379 91235 01938725 4837991235
## 733 48 417 90030 01938481 4841790030
## 734 48 417 92640 01939009 4841792640
## 735 48 411 93231 01939170 4841193231
## 736 48 411 93439 01939171 4841193439
## 737 48 489 92155 01938912 4848992155
## 738 48 489 93435 01939169 4848993435
## 739 48 113 93682 01939217 4811393682
## 740 48 459 90280 01938531 4845990280
## 741 48 459 91525 01938782 4845991525
## 742 48 225 90900 01938658 4822590900
## 743 48 225 91635 01938804 4822591635
## 744 48 225 92310 01938943 4822592310
## 745 48 475 91615 01938800 4847591615
## 746 48 183 91520 01938781 4818391520
## 747 48 183 92275 01938936 4818392275
## 748 48 183 92020 01938885 4818392020
## 749 48 183 92093 01938937 4818392093
## 750 48 207 93360 01939154 4820793360
## 751 48 207 93390 01939160 4820793390
## 752 48 253 90110 01938497 4825390110
## 753 48 253 92320 01938945 4825392320
## 754 48 313 92370 01938955 4831392370
## 755 48 353 93810 01939244 4835393810
## 756 48 483 94190 01939320 4848394190
## 757 48 217 91810 01938843 4821791810
## 758 48 217 92380 01938957 4821792380
## 759 48 217 90355 01938546 4821790355
## 760 48 497 90975 01938673 4849790975
## 761 48 497 90445 01938564 4849790445
## 762 48 497 90060 01938487 4849790060
## 763 48 265 90675 01938613 4826590675
## 764 48 383 90290 01938533 4838390290
## 765 48 301 92525 01938986 4830192525
## 766 48 001 90650 01938605 4800190650
## 767 48 001 92615 01939004 4800192615
## 768 48 001 91390 01938755 4800191390
## 769 48 001 92945 01939070 4800192945
## 770 48 057 93085 01939098 4805793085
## 771 48 057 93105 01939102 4805793105
## 772 48 031 91950 01938871 4803191950
## 773 48 449 92665 01939014 4844992665
## 774 48 485 90525 01938580 4848590525
## 775 48 159 92675 01939016 4815992675
## 776 48 485 94215 01939325 4848594215
## 777 48 307 90405 01938556 4830790405
## 778 48 441 92535 01938988 4844192535
## 779 48 169 93118 01939103 4816993118
## 780 48 059 90180 01938511 4805990180
## 781 48 315 91937 01938964 4831591937
## 782 48 305 93820 01939246 4830593820
## 783 48 213 92150 01938911 4821392150
## 784 48 433 90145 01938504 4843390145
## 785 48 163 92635 01939008 4816392635
## 786 48 163 91055 01938689 4816391055
## 787 48 163 92980 01939077 4816392980
## 788 48 499 92590 01938999 4849992590
## 789 48 467 90620 01938599 4846790620
## 790 48 467 91620 01938801 4846791620
## 791 48 467 94000 01939282 4846794000
## 792 48 041 94150 01939312 4804194150
## 793 48 449 90830 01938644 4844990830
## 794 48 165 93485 01939179 4816593485
## 795 48 165 93520 01939186 4816593520
## 796 48 257 91350 01938747 4825791350
## 797 48 257 93865 01939255 4825793865
## 798 48 287 91505 01938778 4828791505
## 799 48 287 92205 01938922 4828792205
## 800 48 451 94180 01939318 4845194180
## 801 48 089 91095 01938697 4808991095
## 802 48 089 90800 01938638 4808990800
## 803 48 089 94120 01939306 4808994120
## 804 48 329 92560 01938993 4832992560
## 805 48 329 92566 01938994 4832992566
## 806 48 343 92705 01939022 4834392705
## 807 48 343 90940 01938666 4834390940
## 808 48 033 91430 01938763 4803391430
## 809 48 097 91440 01938765 4809791440
## 810 48 097 92680 01939017 4809792680
## 811 48 097 90580 01938591 4809790580
## 812 48 477 91490 01938775 4847791490
## 813 48 051 90570 01938589 4805190570
## 814 48 303 91865 01938854 4830391865
## 815 48 303 93540 01939190 4830393540
## 816 48 409 90125 01938500 4840990125
## 817 48 409 92470 01938975 4840992470
## 818 48 409 93815 01939245 4840993815
## 819 48 409 93580 01939198 4840993580
## 820 48 455 91655 01938808 4845591655
## 821 48 455 93945 01939271 4845593945
## 822 48 447 93910 01939264 4844793910
## 823 48 447 94280 01939338 4844794280
## 824 48 451 93405 01939163 4845193405
## 825 48 213 90155 01938506 4821390155
## 826 48 213 90652 02378355 4821390652
## 827 48 213 90687 01938570 4821390687
## 828 48 207 91735 01938828 4820791735
## 829 48 207 93285 01939138 4820793285
## 830 48 207 94125 01939307 4820794125
## 831 48 013 90695 01938617 4801390695
## 832 48 013 93120 01939105 4801393120
## 833 48 013 91955 01938872 4801391955
## 834 48 013 93070 01939095 4801393070
## 835 48 367 94105 01939303 4836794105
## 836 48 355 91080 01938694 4835591080
## 837 48 355 93270 01939135 4835593270
## 838 48 437 91700 01938821 4843791700
## 839 48 437 93955 01939273 4843793955
## 840 48 505 93455 01939173 4850593455
## 841 48 505 94310 01939344 4850594310
## 842 48 027 90255 01938526 4802790255
## 843 48 027 92030 01938887 4802792030
## 844 48 027 93630 01939208 4802793630
## 845 48 043 90040 01938483 4804390040
## 846 48 043 92390 01938959 4804392390
## 847 48 265 92015 01938884 4826592015
## 848 48 071 92620 01939005 4807192620
## 849 48 071 90075 01938490 4807190075
## 850 48 229 90990 01938676 4822990990
## 851 48 459 90295 01938534 4845990295
## 852 48 459 92920 01939065 4845992920
## 853 48 459 91515 01938780 4845991515
## 854 48 357 93005 01939082 4835793005
## 855 48 357 93010 01939083 4835793010
## 856 48 099 91270 01938731 4809991270
## 857 48 099 91480 01938773 4809991480
## 858 48 099 93965 01939275 4809993965
## 859 48 399 93350 01939152 4839993350
## 860 48 399 92585 01938998 4839992585
## 861 48 099 91370 01938751 4809991370
## NAME NAMELSAD LSAD
## 0 Gorman Gorman CCD 22
## 1 Ranger Ranger CCD 22
## 2 Eastland Eastland CCD 22
## 3 Rising Star Rising Star CCD 22
## 4 Spur Spur CCD 22
## 5 Dickens Dickens CCD 22
## 6 Channing Channing CCD 22
## 7 Hereford East Hereford East CCD 22
## 8 Hereford West Hereford West CCD 22
## 9 Ropesville Ropesville CCD 22
## 10 Realitos-Concepcion Realitos-Concepcion CCD 22
## 11 Benavides Benavides CCD 22
## 12 Paris Paris CCD 22
## 13 Briggs Briggs CCD 22
## 14 Normangee Normangee CCD 22
## 15 Troup-Arp Troup-Arp CCD 22
## 16 Whitehouse Whitehouse CCD 22
## 17 Tyler Tyler CCD 22
## 18 Winona Winona CCD 22
## 19 Angleton Angleton CCD 22
## 20 Alvin-Pearland Alvin-Pearland CCD 22
## 21 Brazosport Brazosport CCD 22
## 22 Hamlin Hamlin CCD 22
## 23 Del Rio Del Rio CCD 22
## 24 Del Rio Northeast Del Rio Northeast CCD 22
## 25 Del Rio Northwest Del Rio Northwest CCD 22
## 26 Stamford Stamford CCD 22
## 27 Crowell Crowell CCD 22
## 28 Thalia Thalia CCD 22
## 29 Anton Anton CCD 22
## 30 Sundown Sundown CCD 22
## 31 Boerne Boerne CCD 22
## 32 Kosse Kosse CCD 22
## 33 Prairie Hill Prairie Hill CCD 22
## 34 Groesbeck Groesbeck CCD 22
## 35 Personville Personville CCD 22
## 36 Thornton Thornton CCD 22
## 37 Miami Miami CCD 22
## 38 Imperial Imperial CCD 22
## 39 Fort Stockton Fort Stockton CCD 22
## 40 Mason West Mason West CCD 22
## 41 Barstow-Pyote Barstow-Pyote CCD 22
## 42 Monahans Monahans CCD 22
## 43 Lake O' the Pines Lake O' the Pines CCD 22
## 44 Comfort Comfort CCD 22
## 45 Bertram Bertram CCD 22
## 46 Dalhart Dalhart CCD 22
## 47 San Augustine San Augustine CCD 22
## 48 Texline Texline CCD 22
## 49 Victoria Victoria CCD 22
## 50 Victoria West Victoria West CCD 22
## 51 Vega Vega CCD 22
## 52 Fulton Fulton CCD 22
## 53 New Boston New Boston CCD 22
## 54 Kamey-Sixmile Kamey-Sixmile CCD 22
## 55 Clyde Clyde CCD 22
## 56 La Marque-Hitchcock La Marque-Hitchcock CCD 22
## 57 Hooks Hooks CCD 22
## 58 Farwell-Bovina Farwell-Bovina CCD 22
## 59 Friona Friona CCD 22
## 60 Falfurrias Falfurrias CCD 22
## 61 Encino Encino CCD 22
## 62 Cuero Cuero CCD 22
## 63 Yorktown Yorktown CCD 22
## 64 Westhoff-Arneckville Westhoff-Arneckville CCD 22
## 65 Yoakum Yoakum CCD 22
## 66 Sunray Sunray CCD 22
## 67 Hallettsville Hallettsville CCD 22
## 68 Yoakum Yoakum CCD 22
## 69 Shiner Shiner CCD 22
## 70 Bangs Bangs CCD 22
## 71 Brownwood Brownwood CCD 22
## 72 Blanket Blanket CCD 22
## 73 Dimmitt Dimmitt CCD 22
## 74 Falls City Falls City CCD 22
## 75 Kenedy Kenedy CCD 22
## 76 Seymour Rural Seymour Rural CCD 22
## 77 Harwood-Ottine Harwood-Ottine CCD 22
## 78 Navasota Navasota CCD 22
## 79 Fort Hancock Fort Hancock CCD 22
## 80 Mertzon North Mertzon North CCD 22
## 81 Fort Davis Fort Davis CCD 22
## 82 Hawley-Noodle Hawley-Noodle CCD 22
## 83 Jayton South Jayton South CCD 22
## 84 Lampasas Lampasas CCD 22
## 85 Coolidge Coolidge CCD 22
## 86 Bishop Bishop CCD 22
## 87 Calvert Calvert CCD 22
## 88 Winters Winters CCD 22
## 89 La Grulla La Grulla CCD 22
## 90 Victoria South Victoria South CCD 22
## 91 Iowa Park Iowa Park CCD 22
## 92 Crystal City Crystal City CCD 22
## 93 Copperas Cove Copperas Cove CCD 22
## 94 Oglesby Oglesby CCD 22
## 95 Purmela-Levita Purmela-Levita CCD 22
## 96 Runge Runge CCD 22
## 97 Gillett Gillett CCD 22
## 98 Karnes City Karnes City CCD 22
## 99 North Motley North Motley CCD 22
## 100 Port Arthur Port Arthur CCD 22
## 101 Sabine Pass Sabine Pass CCD 22
## 102 Cranfills Gap Cranfills Gap CCD 22
## 103 Meridian Meridian CCD 22
## 104 Encinal Encinal CCD 22
## 105 Crane North Crane North CCD 22
## 106 Buna Buna CCD 22
## 107 Goliad South Goliad South CCD 22
## 108 Weesatche-Ander Weesatche-Ander CCD 22
## 109 Goree Goree CCD 22
## 110 Munday Munday CCD 22
## 111 Fulshear-Simonton Fulshear-Simonton CCD 22
## 112 Rosenberg-Richmond Rosenberg-Richmond CCD 22
## 113 Stafford-Missouri City Stafford-Missouri City CCD 22
## 114 Benjamin Benjamin CCD 22
## 115 Robert Lee Robert Lee CCD 22
## 116 Bronte Bronte CCD 22
## 117 San Antonio East San Antonio East CCD 22
## 118 San Antonio North San Antonio North CCD 22
## 119 San Antonio Northeast San Antonio Northeast CCD 22
## 120 San Antonio Northwest San Antonio Northwest CCD 22
## 121 San Antonio South San Antonio South CCD 22
## 122 San Antonio West San Antonio West CCD 22
## 123 Huntsville Huntsville CCD 22
## 124 Point Blank Point Blank CCD 22
## 125 Coldspring Coldspring CCD 22
## 126 Clifton Clifton CCD 22
## 127 Valley Mills Valley Mills CCD 22
## 128 Ennis Ennis CCD 22
## 129 Maypearl Maypearl CCD 22
## 130 De Kalb De Kalb CCD 22
## 131 Maud-Redwater Maud-Redwater CCD 22
## 132 Dalby Springs-Simms Dalby Springs-Simms CCD 22
## 133 Texarkana Texarkana CCD 22
## 134 Childress Childress CCD 22
## 135 North Childress North Childress CCD 22
## 136 Marble Falls Marble Falls CCD 22
## 137 Burnet Burnet CCD 22
## 138 Itasca Itasca CCD 22
## 139 Whitney Whitney CCD 22
## 140 Granbury East Granbury East CCD 22
## 141 Beeville Beeville CCD 22
## 142 Pettus-Pawnee Pettus-Pawnee CCD 22
## 143 Wortham Wortham CCD 22
## 144 Galveston Galveston CCD 22
## 145 Iredell Iredell CCD 22
## 146 Eagle Pass Eagle Pass CCD 22
## 147 Quemado Quemado CCD 22
## 148 Burleson-Joshua Burleson-Joshua CCD 22
## 149 Grandview Grandview CCD 22
## 150 Cleburne Cleburne CCD 22
## 151 Alvarado Alvarado CCD 22
## 152 Godley Godley CCD 22
## 153 Hallsville Hallsville CCD 22
## 154 Waskom Waskom CCD 22
## 155 Texas City-League City Texas City-League City CCD 22
## 156 Bolivar Peninsula Bolivar Peninsula CCD 22
## 157 Fluvanna-Ira Fluvanna-Ira CCD 22
## 158 Riviera Riviera CCD 22
## 159 Hermleigh Hermleigh CCD 22
## 160 Anna Anna CCD 22
## 161 Farmersville Farmersville CCD 22
## 162 Plano Plano CCD 22
## 163 Nevada Nevada CCD 22
## 164 Blue Ridge Blue Ridge CCD 22
## 165 McKinney McKinney CCD 22
## 166 Celina Celina CCD 22
## 167 Lyford Lyford CCD 22
## 168 Sebastian Sebastian CCD 22
## 169 Raymondville Raymondville CCD 22
## 170 Ector Ector CCD 22
## 171 Leonard Leonard CCD 22
## 172 Bonham Bonham CCD 22
## 173 Northwest Rockwall Northwest Rockwall CCD 22
## 174 Sarita Sarita CCD 22
## 175 Dodd City Dodd City CCD 22
## 176 Ladonia Ladonia CCD 22
## 177 Honey Grove Honey Grove CCD 22
## 178 Flatonia Flatonia CCD 22
## 179 Round Top Round Top CCD 22
## 180 Fayetteville Fayetteville CCD 22
## 181 Mauriceville Mauriceville CCD 22
## 182 Orange Orange CCD 22
## 183 Bridge City-Orangefield Bridge City-Orangefield CCD 22
## 184 Carrizo Springs Carrizo Springs CCD 22
## 185 Asherton Asherton CCD 22
## 186 Marlin Marlin CCD 22
## 187 Reagan Reagan CCD 22
## 188 Mullin-Priddy Mullin-Priddy CCD 22
## 189 La Grange West La Grange West CCD 22
## 190 Justin-Roanoke Justin-Roanoke CCD 22
## 191 Pilot Point-Aubrey Pilot Point-Aubrey CCD 22
## 192 Kingsville Kingsville CCD 22
## 193 Carthage Carthage CCD 22
## 194 Gary City Gary City CCD 22
## 195 Long Branch-Dotson Long Branch-Dotson CCD 22
## 196 Freer Freer CCD 22
## 197 San Diego San Diego CCD 22
## 198 Rocksprings South Rocksprings South CCD 22
## 199 Flat Flat CCD 22
## 200 Crane South Crane South CCD 22
## 201 Crosbyton Crosbyton CCD 22
## 202 Princeton Princeton CCD 22
## 203 Wellington Wellington CCD 22
## 204 Garwood Garwood CCD 22
## 205 Eola-Paint Rock Eola-Paint Rock CCD 22
## 206 Valley View Valley View CCD 22
## 207 Canyon Lake Canyon Lake CCD 22
## 208 De Leon De Leon CCD 22
## 209 Castroville-LaCoste Castroville-LaCoste CCD 22
## 210 Hondo Hondo CCD 22
## 211 Schulenburg Schulenburg CCD 22
## 212 La Grange La Grange CCD 22
## 213 Lexington Lexington CCD 22
## 214 West Crockett West Crockett CCD 22
## 215 Morton Morton CCD 22
## 216 Ben Wheeler-Edom Ben Wheeler-Edom CCD 22
## 217 Edgewood Edgewood CCD 22
## 218 Wills Point Wills Point CCD 22
## 219 Cedar Creek Lake Cedar Creek Lake CCD 22
## 220 Roma-Los Saenz Roma-Los Saenz CCD 22
## 221 Rio Grande City Rio Grande City CCD 22
## 222 Luling Luling CCD 22
## 223 Muleshoe Muleshoe CCD 22
## 224 Skidmore Skidmore CCD 22
## 225 Bowie Bowie CCD 22
## 226 St. Jo St. Jo CCD 22
## 227 Nocona Nocona CCD 22
## 228 Andrews North Andrews North CCD 22
## 229 Andrews South Andrews South CCD 22
## 230 Elkhart Elkhart CCD 22
## 231 Lufkin Lufkin CCD 22
## 232 Campbellton Campbellton CCD 22
## 233 Northwest Grayson Northwest Grayson CCD 22
## 234 Holliday Holliday CCD 22
## 235 Snyder Snyder CCD 22
## 236 Burlington Burlington CCD 22
## 237 Gause-Milano Gause-Milano CCD 22
## 238 Buckholts Buckholts CCD 22
## 239 Rockdale Rockdale CCD 22
## 240 Thorndale Thorndale CCD 22
## 241 Orange Grove-Sandia Orange Grove-Sandia CCD 22
## 242 Northeast Rockwall Northeast Rockwall CCD 22
## 243 South Rockwall South Rockwall CCD 22
## 244 Matagorda-Sargent Matagorda-Sargent CCD 22
## 245 Levelland Levelland CCD 22
## 246 Quitaque Quitaque CCD 22
## 247 George West George West CCD 22
## 248 Chillicothe Chillicothe CCD 22
## 249 Canadian South Canadian South CCD 22
## 250 Cotulla Cotulla CCD 22
## 251 Vidor Vidor CCD 22
## 252 Kountze Kountze CCD 22
## 253 Sour Lake Sour Lake CCD 22
## 254 Lorenzo Lorenzo CCD 22
## 255 East Terrell East Terrell CCD 22
## 256 Greenville Greenville CCD 22
## 257 Wolfe City Wolfe City CCD 22
## 258 Celeste Celeste CCD 22
## 259 Quinlan Quinlan CCD 22
## 260 Lubbock Lubbock CCD 22
## 261 Slaton Slaton CCD 22
## 262 Canadian North Canadian North CCD 22
## 263 Ballinger Ballinger CCD 22
## 264 Floydada Floydada CCD 22
## 265 Lockney Lockney CCD 22
## 266 Amarillo Amarillo CCD 22
## 267 Stratford Stratford CCD 22
## 268 East Crockett East Crockett CCD 22
## 269 Ralls Ralls CCD 22
## 270 Mertzon South Mertzon South CCD 22
## 271 Sonora Sonora CCD 22
## 272 North Jim Hogg North Jim Hogg CCD 22
## 273 South Jim Hogg South Jim Hogg CCD 22
## 274 Stephenville Stephenville CCD 22
## 275 La Ward-Lolita La Ward-Lolita CCD 22
## 276 Vanderbilt Vanderbilt CCD 22
## 277 Morgan Mill-Bluff Dale Morgan Mill-Bluff Dale CCD 22
## 278 Goliad North Goliad North CCD 22
## 279 Paducah South Paducah South CCD 22
## 280 Paducah North Paducah North CCD 22
## 281 Gustine Gustine CCD 22
## 282 Comanche Comanche CCD 22
## 283 Cost-Wrightsboro Cost-Wrightsboro CCD 22
## 284 Waelder Waelder CCD 22
## 285 Gonzales Gonzales CCD 22
## 286 Nixon Nixon CCD 22
## 287 Smiley Smiley CCD 22
## 288 Guthrie Guthrie CCD 22
## 289 Duffau-Clairette Duffau-Clairette CCD 22
## 290 Tilden Tilden CCD 22
## 291 Mart Mart CCD 22
## 292 East Tom Green East Tom Green CCD 22
## 293 Iraan Iraan CCD 22
## 294 Warren Warren CCD 22
## 295 Portland-Gregory Portland-Gregory CCD 22
## 296 Dublin Dublin CCD 22
## 297 Jasper Jasper CCD 22
## 298 Kirbyville Kirbyville CCD 22
## 299 Lakeview Lakeview CCD 22
## 300 Turkey Turkey CCD 22
## 301 Northwest Bell Northwest Bell CCD 22
## 302 Southwest Bell Southwest Bell CCD 22
## 303 Rogers Rogers CCD 22
## 304 Edinburg Edinburg CCD 22
## 305 Mission Mission CCD 22
## 306 Sullivan City Sullivan City CCD 22
## 307 Blanco Blanco CCD 22
## 308 Cedar Creek Lake Cedar Creek Lake CCD 22
## 309 Kaufman Kaufman CCD 22
## 310 Crandall Crandall CCD 22
## 311 Terrell South Terrell South CCD 22
## 312 Eldorado West Eldorado West CCD 22
## 313 Poth Poth CCD 22
## 314 Stockdale Stockdale CCD 22
## 315 Beaumont Beaumont CCD 22
## 316 Nome-China Nome-China CCD 22
## 317 LaBelle LaBelle CCD 22
## 318 Northeast Harris Northeast Harris CCD 22
## 319 Southeast Harris Southeast Harris CCD 22
## 320 Baytown Baytown CCD 22
## 321 Northwest Harris Northwest Harris CCD 22
## 322 Knox City Knox City CCD 22
## 323 Lamesa Northwest Lamesa Northwest CCD 22
## 324 Lamesa Southwest Lamesa Southwest CCD 22
## 325 Roscoe Roscoe CCD 22
## 326 Blackwell-Nolan Blackwell-Nolan CCD 22
## 327 Kennard-Ratcliff Kennard-Ratcliff CCD 22
## 328 Porter Springs Porter Springs CCD 22
## 329 Edcouch-Elsa Edcouch-Elsa CCD 22
## 330 Puerto Rico-San Manuel Puerto Rico-San Manuel CCD 22
## 331 Byers-Petrolia Byers-Petrolia CCD 22
## 332 Southeast Montgomery Southeast Montgomery CCD 22
## 333 East Bell East Bell CCD 22
## 334 Fort Hood Fort Hood CCD 22
## 335 Temple Temple CCD 22
## 336 Magnolia Magnolia CCD 22
## 337 Glen Rose Glen Rose CCD 22
## 338 Kermit Kermit CCD 22
## 339 Seadrift Seadrift CCD 22
## 340 Floresville Floresville CCD 22
## 341 La Vernia La Vernia CCD 22
## 342 Claude North Claude North CCD 22
## 343 Breckenridge North Breckenridge North CCD 22
## 344 Breckenridge South Breckenridge South CCD 22
## 345 Colorado City Colorado City CCD 22
## 346 Westbrook Westbrook CCD 22
## 347 Henrietta Henrietta CCD 22
## 348 Three Rivers Three Rivers CCD 22
## 349 Littlefield Littlefield CCD 22
## 350 Olton Olton CCD 22
## 351 Louise Louise CCD 22
## 352 East Bernard East Bernard CCD 22
## 353 El Campo El Campo CCD 22
## 354 Premont Premont CCD 22
## 355 Alice Alice CCD 22
## 356 Adamsville Adamsville CCD 22
## 357 Sabinal Sabinal CCD 22
## 358 Uvalde Uvalde CCD 22
## 359 Bellevue-Joy Bellevue-Joy CCD 22
## 360 D'Hanis D'Hanis CCD 22
## 361 Devine-Natalia Devine-Natalia CCD 22
## 362 Laredo North-Webb Laredo North-Webb CCD 22
## 363 Laredo Laredo CCD 22
## 364 Call Call CCD 22
## 365 Deweyville Deweyville CCD 22
## 366 Canyon Canyon CCD 22
## 367 Mineral Wells Mineral Wells CCD 22
## 368 Strawn-Gordon Strawn-Gordon CCD 22
## 369 Spurger Spurger CCD 22
## 370 Woodville Woodville CCD 22
## 371 Colmesneil-Chester Colmesneil-Chester CCD 22
## 372 Ganado Ganado CCD 22
## 373 Edna-Cordele Edna-Cordele CCD 22
## 374 Eldorado East Eldorado East CCD 22
## 375 Harper Harper CCD 22
## 376 South Sand Hills South Sand Hills CCD 22
## 377 Brackettville Brackettville CCD 22
## 378 Pineland Pineland CCD 22
## 379 Milam Milam CCD 22
## 380 La Pryor La Pryor CCD 22
## 381 Claude South Claude South CCD 22
## 382 Samnorwood Samnorwood CCD 22
## 383 Huntington Huntington CCD 22
## 384 Zavalla Zavalla CCD 22
## 385 Diboll Diboll CCD 22
## 386 Pollok Pollok CCD 22
## 387 Lumberton Lumberton CCD 22
## 388 Goodlett Goodlett CCD 22
## 389 Quanah Quanah CCD 22
## 390 San Antonio Central San Antonio Central CCD 22
## 391 Mount Enterprise Mount Enterprise CCD 22
## 392 Tatum Tatum CCD 22
## 393 Laneville Laneville CCD 22
## 394 Kilgore Kilgore CCD 22
## 395 New Braunfels New Braunfels CCD 22
## 396 Hardin-Rye Hardin-Rye CCD 22
## 397 Montgomery Montgomery CCD 22
## 398 Willis Willis CCD 22
## 399 Pickton-Pine Forest Pickton-Pine Forest CCD 22
## 400 Seymore Seymore CCD 22
## 401 Brookshire Brookshire CCD 22
## 402 Harlingen-San Benito Harlingen-San Benito CCD 22
## 403 Chireno-Martinsville Chireno-Martinsville CCD 22
## 404 Nacogdoches Nacogdoches CCD 22
## 405 Cushing-Douglass Cushing-Douglass CCD 22
## 406 Garrison Garrison CCD 22
## 407 Borger Borger CCD 22
## 408 Mason East Mason East CCD 22
## 409 Caddo Mills Caddo Mills CCD 22
## 410 Commerce Commerce CCD 22
## 411 Lone Oak Lone Oak CCD 22
## 412 Llano North Llano North CCD 22
## 413 Sterling City Sterling City CCD 22
## 414 Leesburg-Newsome Leesburg-Newsome CCD 22
## 415 Pittsburg Pittsburg CCD 22
## 416 Fargo-Odell Fargo-Odell CCD 22
## 417 Harleton Harleton CCD 22
## 418 Marshall Marshall CCD 22
## 419 Santa Anna Santa Anna CCD 22
## 420 Coleman Coleman CCD 22
## 421 Clarendon Clarendon CCD 22
## 422 Hedley Hedley CCD 22
## 423 Big Wells Big Wells CCD 22
## 424 Carrollton Carrollton CCD 22
## 425 Denton Denton CCD 22
## 426 Sanger Sanger CCD 22
## 427 The Colony The Colony CCD 22
## 428 Lewisville-Flower Mound Lewisville-Flower Mound CCD 22
## 429 Brazoria-West Columbia Brazoria-West Columbia CCD 22
## 430 Cameron Cameron CCD 22
## 431 Davilla Davilla CCD 22
## 432 Hubbard-Mount Calm Hubbard-Mount Calm CCD 22
## 433 Silverton Silverton CCD 22
## 434 Houston Houston CCD 22
## 435 Pasadena Pasadena CCD 22
## 436 Bogata Bogata CCD 22
## 437 Dalhart Dalhart CCD 22
## 438 Marfa Marfa CCD 22
## 439 Italy Italy CCD 22
## 440 Midlothian Midlothian CCD 22
## 441 Ferris Ferris CCD 22
## 442 Waxahachie Waxahachie CCD 22
## 443 Graham Graham CCD 22
## 444 Olney Olney CCD 22
## 445 Estelline Estelline CCD 22
## 446 Memphis Memphis CCD 22
## 447 Brownfield Brownfield CCD 22
## 448 Meadow Meadow CCD 22
## 449 Saratoga-Batson Saratoga-Batson CCD 22
## 450 Silsbee Silsbee CCD 22
## 451 Southwest Guadalupe Southwest Guadalupe CCD 22
## 452 Granger Granger CCD 22
## 453 Buffalo Buffalo CCD 22
## 454 Oakwood Oakwood CCD 22
## 455 Blooming Grove Blooming Grove CCD 22
## 456 Kerens Kerens CCD 22
## 457 Rice Rice CCD 22
## 458 Stanton Stanton CCD 22
## 459 May May CCD 22
## 460 Whiteface Whiteface CCD 22
## 461 Stinnett Stinnett CCD 22
## 462 Mexia Mexia CCD 22
## 463 Hart Hart CCD 22
## 464 Corsicana Corsicana CCD 22
## 465 Dawson Dawson CCD 22
## 466 Canadian River Breaks Canadian River Breaks CCD 22
## 467 Winnie-Stowell Winnie-Stowell CCD 22
## 468 Southwest Travis Southwest Travis CCD 22
## 469 Northeast Guadalupe Northeast Guadalupe CCD 22
## 470 Schertz-Cibolo Schertz-Cibolo CCD 22
## 471 Southeast Guadalupe Southeast Guadalupe CCD 22
## 472 Seguin Seguin CCD 22
## 473 Adrian Adrian CCD 22
## 474 Chilton Chilton CCD 22
## 475 Perry Perry CCD 22
## 476 Lott Lott CCD 22
## 477 Rosebud Rosebud CCD 22
## 478 Sierra Blanca Sierra Blanca CCD 22
## 479 Jacksonville Jacksonville CCD 22
## 480 Rusk Rusk CCD 22
## 481 Wells Wells CCD 22
## 482 Springtown-Reno Springtown-Reno CCD 22
## 483 Weatherford Northwest Weatherford Northwest CCD 22
## 484 Bryson Bryson CCD 22
## 485 Perrin Perrin CCD 22
## 486 Higgins Higgins CCD 22
## 487 Booker Booker CCD 22
## 488 Follett Follett CCD 22
## 489 Camp Wood-Leakey Camp Wood-Leakey CCD 22
## 490 Deport Deport CCD 22
## 491 Howland Howland CCD 22
## 492 Sumner Sumner CCD 22
## 493 Texhoma Texhoma CCD 22
## 494 Matador Matador CCD 22
## 495 Llano South Llano South CCD 22
## 496 Shamrock Shamrock CCD 22
## 497 East Grayson East Grayson CCD 22
## 498 Southwest Grayson Southwest Grayson CCD 22
## 499 West Terrell West Terrell CCD 22
## 500 Goldthwaite Goldthwaite CCD 22
## 501 Earth Earth CCD 22
## 502 Sudan-Amherst Sudan-Amherst CCD 22
## 503 Dumas Dumas CCD 22
## 504 Denver City Denver City CCD 22
## 505 Corpus Christi Corpus Christi CCD 22
## 506 Amarillo Amarillo CCD 22
## 507 Batesville Batesville CCD 22
## 508 Corpus Christi West Corpus Christi West CCD 22
## 509 Laredo South-El Cenizo Laredo South-El Cenizo CCD 22
## 510 Port Aransas Port Aransas CCD 22
## 511 Kress Kress CCD 22
## 512 Austwell-Tivoli Austwell-Tivoli CCD 22
## 513 Refugio Refugio CCD 22
## 514 Woodsboro Woodsboro CCD 22
## 515 Price-Turnertown Price-Turnertown CCD 22
## 516 Overton Overton CCD 22
## 517 Pinehill Pinehill CCD 22
## 518 Hemphill Hemphill CCD 22
## 519 Bivins-McLeod Bivins-McLeod CCD 22
## 520 Marietta-Douglassville Marietta-Douglassville CCD 22
## 521 East Cameron East Cameron CCD 22
## 522 Rio Hondo Rio Hondo CCD 22
## 523 Brownsville Brownsville CCD 22
## 524 Los Fresnos-Laureles Los Fresnos-Laureles CCD 22
## 525 Burkeville Burkeville CCD 22
## 526 Newton Newton CCD 22
## 527 Cisco Cisco CCD 22
## 528 Boyd-Rhome Boyd-Rhome CCD 22
## 529 Van Horn Van Horn CCD 22
## 530 Lometa Lometa CCD 22
## 531 Valentine Valentine CCD 22
## 532 Kyle-Buda Kyle-Buda CCD 22
## 533 Abernathy Abernathy CCD 22
## 534 Hale Center Hale Center CCD 22
## 535 Petersburg Petersburg CCD 22
## 536 Plainview Plainview CCD 22
## 537 El Paso El Paso CCD 22
## 538 El Paso Northwest El Paso Northwest CCD 22
## 539 El Paso North Central El Paso North Central CCD 22
## 540 Graford Graford CCD 22
## 541 Palo Pinto-Santo Palo Pinto-Santo CCD 22
## 542 Boling-Newgulf Boling-Newgulf CCD 22
## 543 Wharton Wharton CCD 22
## 544 Montague-Forestburg Montague-Forestburg CCD 22
## 545 Panhandle Panhandle CCD 22
## 546 White Deer-Groom White Deer-Groom CCD 22
## 547 Granbury West Granbury West CCD 22
## 548 Bastrop Bastrop CCD 22
## 549 Smithville Smithville CCD 22
## 550 El Paso East El Paso East CCD 22
## 551 Longview Longview CCD 22
## 552 Liberty City Liberty City CCD 22
## 553 West Odessa-Goldsmith West Odessa-Goldsmith CCD 22
## 554 Rockport Rockport CCD 22
## 555 Ravenna-Telephone Ravenna-Telephone CCD 22
## 556 Moulton Moulton CCD 22
## 557 Sonora Rural Sonora Rural CCD 22
## 558 Broaddus Broaddus CCD 22
## 559 Hamilton Hamilton CCD 22
## 560 Hico Hico CCD 22
## 561 Fairfield Fairfield CCD 22
## 562 Gruver Gruver CCD 22
## 563 Spearman Spearman CCD 22
## 564 Atlanta Atlanta CCD 22
## 565 Butler Butler CCD 22
## 566 Teague Teague CCD 22
## 567 Pecos Pecos CCD 22
## 568 Balmorhea Balmorhea CCD 22
## 569 Gainesville Gainesville CCD 22
## 570 Alba Alba CCD 22
## 571 Hawkins Hawkins CCD 22
## 572 Winnsboro Winnsboro CCD 22
## 573 Quitman Quitman CCD 22
## 574 Centerville Centerville CCD 22
## 575 Marquez Marquez CCD 22
## 576 Northeast Travis Northeast Travis CCD 22
## 577 Northwest Travis Northwest Travis CCD 22
## 578 Austin Austin CCD 22
## 579 Ingram Ingram CCD 22
## 580 Henderson Henderson CCD 22
## 581 Point Point CCD 22
## 582 Bryan-College Station Bryan-College Station CCD 22
## 583 South Brazos South Brazos CCD 22
## 584 Northeast Brazos Northeast Brazos CCD 22
## 585 Linden Linden CCD 22
## 586 Hughes Springs-Avinger Hughes Springs-Avinger CCD 22
## 587 Lefors Lefors CCD 22
## 588 McLean McLean CCD 22
## 589 Pampa Pampa CCD 22
## 590 Weatherford Weatherford CCD 22
## 591 Bandera Bandera CCD 22
## 592 Medina Medina CCD 22
## 593 Cleveland Cleveland CCD 22
## 594 Liberty-Dayton Liberty-Dayton CCD 22
## 595 Daisetta Daisetta CCD 22
## 596 Menard East Menard East CCD 22
## 597 Menard West Menard West CCD 22
## 598 North Zulch North Zulch CCD 22
## 599 Midway Midway CCD 22
## 600 Aspermont South Aspermont South CCD 22
## 601 Palacios Palacios CCD 22
## 602 Bay City Bay City CCD 22
## 603 McCaulley McCaulley CCD 22
## 604 Rotan Rotan CCD 22
## 605 Roby Roby CCD 22
## 606 Fredericksburg Fredericksburg CCD 22
## 607 Stonewall Stonewall CCD 22
## 608 Riverside Riverside CCD 22
## 609 Cooks Point Cooks Point CCD 22
## 610 Old River Old River CCD 22
## 611 Somerville Somerville CCD 22
## 612 Post East Post East CCD 22
## 613 O'Donnell O'Donnell CCD 22
## 614 Tidehaven Tidehaven CCD 22
## 615 Electra Electra CCD 22
## 616 Hempstead Hempstead CCD 22
## 617 Prairie View-Waller Prairie View-Waller CCD 22
## 618 Gail North Gail North CCD 22
## 619 Van Horn Rural Van Horn Rural CCD 22
## 620 Big Spring Big Spring CCD 22
## 621 McCamey McCamey CCD 22
## 622 Rankin Rankin CCD 22
## 623 Cross Plains Cross Plains CCD 22
## 624 New Waverly New Waverly CCD 22
## 625 Lockhart Lockhart CCD 22
## 626 Martindale Martindale CCD 22
## 627 Wilson Wilson CCD 22
## 628 Brenham Brenham CCD 22
## 629 Washington-Chappell Hill Washington-Chappell Hill CCD 22
## 630 Burton Burton CCD 22
## 631 Jacksboro Jacksboro CCD 22
## 632 Round Rock-Georgetown Round Rock-Georgetown CCD 22
## 633 Cedar Park-Liberty Hill Cedar Park-Liberty Hill CCD 22
## 634 Blossom Blossom CCD 22
## 635 Powderly Powderly CCD 22
## 636 Biardstown Biardstown CCD 22
## 637 Roxton Roxton CCD 22
## 638 Fort Worth Fort Worth CCD 22
## 639 China Spring China Spring CCD 22
## 640 McGregor McGregor CCD 22
## 641 Waco Waco CCD 22
## 642 Crawford Crawford CCD 22
## 643 Elm Mott Elm Mott CCD 22
## 644 West West CCD 22
## 645 Moody-Lorena Moody-Lorena CCD 22
## 646 Axtell Axtell CCD 22
## 647 Florence Florence CCD 22
## 648 Taylor Taylor CCD 22
## 649 Jarrell Jarrell CCD 22
## 650 Eden-Millersview Eden-Millersview CCD 22
## 651 De Berry-Deadwood De Berry-Deadwood CCD 22
## 652 Beckville Beckville CCD 22
## 653 Jean-Loving Jean-Loving CCD 22
## 654 Newcastle Newcastle CCD 22
## 655 Hearne Hearne CCD 22
## 656 Bremond Bremond CCD 22
## 657 Franklin Franklin CCD 22
## 658 Abilene Abilene CCD 22
## 659 Jim Ned Jim Ned CCD 22
## 660 Junction Southeast Junction Southeast CCD 22
## 661 Glendale Glendale CCD 22
## 662 Apple Springs Apple Springs CCD 22
## 663 Rocksprings North Rocksprings North CCD 22
## 664 Melvin Melvin CCD 22
## 665 Rochelle Rochelle CCD 22
## 666 Harrold-Oklaunion Harrold-Oklaunion CCD 22
## 667 Lockett Lockett CCD 22
## 668 Vernon Vernon CCD 22
## 669 Northeast Dallas Northeast Dallas CCD 22
## 670 Plains Plains CCD 22
## 671 Archer City Archer City CCD 22
## 672 San Marcos San Marcos CCD 22
## 673 Dripping Springs-Wimberley Dripping Springs-Wimberley CCD 22
## 674 Bellville Bellville CCD 22
## 675 Wallis Wallis CCD 22
## 676 Sealy Sealy CCD 22
## 677 Industry Industry CCD 22
## 678 Pecan Gap Pecan Gap CCD 22
## 679 Center Center CCD 22
## 680 Cooper Cooper CCD 22
## 681 Timpson Timpson CCD 22
## 682 Cedar Creek-Red Rock Cedar Creek-Red Rock CCD 22
## 683 Elgin Elgin CCD 22
## 684 Clarksville Clarksville CCD 22
## 685 Talpa Talpa CCD 22
## 686 Novice Novice CCD 22
## 687 Winnsboro Winnsboro CCD 22
## 688 Hargill Hargill CCD 22
## 689 McAllen-Pharr McAllen-Pharr CCD 22
## 690 Southeast Hidalgo Southeast Hidalgo CCD 22
## 691 Seymour Seymour CCD 22
## 692 Alto Alto CCD 22
## 693 Mount Selman Mount Selman CCD 22
## 694 New Summerfield New Summerfield CCD 22
## 695 Annona-Avery Annona-Avery CCD 22
## 696 Manchester Manchester CCD 22
## 697 Detroit Detroit CCD 22
## 698 Presidio Presidio CCD 22
## 699 North Hopkins-Sulphur Bluff North Hopkins-Sulphur Bluff CCD 22
## 700 Arlington Arlington CCD 22
## 701 Northeast Tarrant Northeast Tarrant CCD 22
## 702 Junction Northwest Junction Northwest CCD 22
## 703 Loraine Loraine CCD 22
## 704 Shepherd-Evergreen Shepherd-Evergreen CCD 22
## 705 Big Spring North Big Spring North CCD 22
## 706 Coahoma Coahoma CCD 22
## 707 Talco Talco CCD 22
## 708 Winfield Winfield CCD 22
## 709 Lamesa Southeast Lamesa Southeast CCD 22
## 710 Lamesa Lamesa CCD 22
## 711 Lamesa Northeast Lamesa Northeast CCD 22
## 712 Cumby Cumby CCD 22
## 713 Sulphur Springs Sulphur Springs CCD 22
## 714 Corrigan Corrigan CCD 22
## 715 Anderson-Bedias Anderson-Bedias CCD 22
## 716 Shelbyville Shelbyville CCD 22
## 717 Tenaha-Joaquin Tenaha-Joaquin CCD 22
## 718 Aiken-Neuville Aiken-Neuville CCD 22
## 719 Bullard Bullard CCD 22
## 720 Lindale Lindale CCD 22
## 721 Tyler East Tyler East CCD 22
## 722 Orchard-Kendleton Orchard-Kendleton CCD 22
## 723 Sugar Land Sugar Land CCD 22
## 724 Needville Needville CCD 22
## 725 Garden City South Garden City South CCD 22
## 726 Garden City North Garden City North CCD 22
## 727 Livingston-Onalaska Livingston-Onalaska CCD 22
## 728 Odessa Odessa CCD 22
## 729 Jayton North Jayton North CCD 22
## 730 Tarzan-Lenorah Tarzan-Lenorah CCD 22
## 731 Wink Wink CCD 22
## 732 Emory Emory CCD 22
## 733 Albany Albany CCD 22
## 734 Moran Moran CCD 22
## 735 Richland Springs Richland Springs CCD 22
## 736 San Saba San Saba CCD 22
## 737 Lasara Lasara CCD 22
## 738 San Perlita San Perlita CCD 22
## 739 Southwest Dallas Southwest Dallas CCD 22
## 740 Bettie Bettie CCD 22
## 741 Gladewater Gladewater CCD 22
## 742 Crockett Crockett CCD 22
## 743 Grapeland Grapeland CCD 22
## 744 Lovelady Lovelady CCD 22
## 745 Grandfalls Grandfalls CCD 22
## 746 Gladewater Gladewater CCD 22
## 747 Longview Northwest Longview Northwest CCD 22
## 748 Kilgore Kilgore CCD 22
## 749 Lakeport Lakeport CCD 22
## 750 Rule Rule CCD 22
## 751 Sagerton Sagerton CCD 22
## 752 Anson Anson CCD 22
## 753 Lueders Lueders CCD 22
## 754 Madisonville Madisonville CCD 22
## 755 Sweetwater Sweetwater CCD 22
## 756 Wheeler Wheeler CCD 22
## 757 Hillsboro Hillsboro CCD 22
## 758 Malone-Penelope Malone-Penelope CCD 22
## 759 Blum Blum CCD 22
## 760 Decatur Decatur CCD 22
## 761 Bridgeport Bridgeport CCD 22
## 762 Alvord Alvord CCD 22
## 763 Center Point Center Point CCD 22
## 764 Big Lake Big Lake CCD 22
## 765 Mentone Mentone CCD 22
## 766 Cayuga Cayuga CCD 22
## 767 Montalba-Tennessee Colony Montalba-Tennessee Colony CCD 22
## 768 Frankston Frankston CCD 22
## 769 Palestine Palestine CCD 22
## 770 Point Comfort Point Comfort CCD 22
## 771 Port Lavaca Port Lavaca CCD 22
## 772 Johnson City Johnson City CCD 22
## 773 Mount Pleasant Mount Pleasant CCD 22
## 774 Burkburnett Burkburnett CCD 22
## 775 Mount Vernon Mount Vernon CCD 22
## 776 Wichita Falls Wichita Falls CCD 22
## 777 Brady Brady CCD 22
## 778 Merkel Merkel CCD 22
## 779 Post West Post West CCD 22
## 780 Baird Baird CCD 22
## 781 Jefferson Jefferson CCD 22
## 782 Tahoka Tahoka CCD 22
## 783 LaRue-Poynor LaRue-Poynor CCD 22
## 784 Aspermont North Aspermont North CCD 22
## 785 Moore Moore CCD 22
## 786 Dilley Dilley CCD 22
## 787 Pearsall Pearsall CCD 22
## 788 Mineola Mineola CCD 22
## 789 Canton Canton CCD 22
## 790 Grand Saline Grand Saline CCD 22
## 791 Van Van CCD 22
## 792 West Brazos West Brazos CCD 22
## 793 Cookville Cookville CCD 22
## 794 Seagraves Seagraves CCD 22
## 795 Seminole Seminole CCD 22
## 796 Forney Forney CCD 22
## 797 Terrell Terrell CCD 22
## 798 Giddings Giddings CCD 22
## 799 Lincoln-Dime Box Lincoln-Dime Box CCD 22
## 800 West Tom Green West Tom Green CCD 22
## 801 Eagle Lake Eagle Lake CCD 22
## 802 Columbus Columbus CCD 22
## 803 Weimar Weimar CCD 22
## 804 Midland Midland CCD 22
## 805 Midland South Midland South CCD 22
## 806 Naples Naples CCD 22
## 807 Daingerfield Daingerfield CCD 22
## 808 Gail South Gail South CCD 22
## 809 Gainesville Southeast Gainesville Southeast CCD 22
## 810 Muenster Muenster CCD 22
## 811 Callisburg Callisburg CCD 22
## 812 Gay Hill-Independence Gay Hill-Independence CCD 22
## 813 Caldwell Caldwell CCD 22
## 814 Idalou Idalou CCD 22
## 815 Shallowater Shallowater CCD 22
## 816 Aransas Pass-Ingleside Aransas Pass-Ingleside CCD 22
## 817 Mathis Mathis CCD 22
## 818 Taft Taft CCD 22
## 819 Sinton-Odem Sinton-Odem CCD 22
## 820 Groveton Groveton CCD 22
## 821 Trinity Trinity CCD 22
## 822 Throckmorton Throckmorton CCD 22
## 823 Woodson Woodson CCD 22
## 824 San Angelo San Angelo CCD 22
## 825 Athens Athens CCD 22
## 826 Cedar Creek Lake Cedar Creek Lake CCD 22
## 827 Chandler-Brownsboro Chandler-Brownsboro CCD 22
## 828 Haskell Haskell CCD 22
## 829 Rochester Rochester CCD 22
## 830 Weinert Weinert CCD 22
## 831 Charlotte Charlotte CCD 22
## 832 Poteet Poteet CCD 22
## 833 Jourdanton Jourdanton CCD 22
## 834 Pleasanton Pleasanton CCD 22
## 835 Weatherford Southeast Weatherford Southeast CCD 22
## 836 Driscoll Driscoll CCD 22
## 837 Robstown Robstown CCD 22
## 838 Happy Happy CCD 22
## 839 Tulia Tulia CCD 22
## 840 San Ygnacio San Ygnacio CCD 22
## 841 Zapata Zapata CCD 22
## 842 Belton Belton CCD 22
## 843 Killeen Killeen CCD 22
## 844 South Bell South Bell CCD 22
## 845 Alpine Alpine CCD 22
## 846 Marathon Marathon CCD 22
## 847 Kerrville Kerrville CCD 22
## 848 Mont Belvieu Mont Belvieu CCD 22
## 849 Anahuac Anahuac CCD 22
## 850 Dell City Dell City CCD 22
## 851 Big Sandy Big Sandy CCD 22
## 852 Ore City Ore City CCD 22
## 853 Gilmer Gilmer CCD 22
## 854 Perryton East Perryton East CCD 22
## 855 Perryton West Perryton West CCD 22
## 856 Evant Evant CCD 22
## 857 Gatesville Gatesville CCD 22
## 858 Turnersville Turnersville CCD 22
## 859 Rowena Rowena CCD 22
## 860 Miles Miles CCD 22
## 861 Fort Hood Fort Hood CCD 22
## CLASSFP MTFCC CNECTAFP NECTAFP NCTADVFP FUNCSTAT ALAND AWATER
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## 8 Z5 G4040 <NA> <NA> <NA> S 2765934478 2868427
## 9 Z5 G4040 <NA> <NA> <NA> S 358638118 0
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## 11 Z5 G4040 <NA> <NA> <NA> S 1403835783 549463
## 12 Z5 G4040 <NA> <NA> <NA> S 245131603 5837124
## 13 Z5 G4040 <NA> <NA> <NA> S 582717970 2224499
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## 15 Z5 G4040 <NA> <NA> <NA> S 286594594 17959984
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## 20 Z5 G4040 <NA> <NA> <NA> S 1062971532 71538223
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## 50 Z5 G4040 <NA> <NA> <NA> S 812163423 11181572
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## 53 Z5 G4040 <NA> <NA> <NA> S 256035273 3131911
## 54 Z5 G4040 <NA> <NA> <NA> S 185913444 5517298
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## 113 Z5 G4040 <NA> <NA> <NA> S 216467997 6440626
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Análise Bivariada
Discuta sobre alguns dos relacionamentos observados nesta parte da investigação. Como os atributos de interesse variaram no conjunto de dados?
Você observou algum relacionamento interessante entre os outros atributos (os que não são de interesse)?
Qual foi o relacionamento mais forte encontrado?
Seção de Gráficos Multivariados
## Warning: Removed 113 rows containing missing values (geom_point).
Análise Multivariada
Discuta sobre os relacionamentos observados nesta parte da investigação. Quais atributos que fortaleceram os demais na observação das variáveis de interesse?
Interações surpreendentes e/ou interessantes foram encontradas entre os atributos?
OPCIONAL: Modelos foram criados usando este conjunto de dados? Discuta sobre os pontos fortes e as limitações do seu modelo.
Gráficos Finais e Sumário
Primeiro Gráfico
Descrição do Primeiro Gráfico
Segundo Gráfico
Descrição do Segundo Gráfico
Terceiro Gráfico
Descrição do Terceiro Gráfico
Reflexão
No início da análise dos dados tinha em mente fazer utilização apenas dos dados disponíveis no dataset. A partir dele comecei a fazer a análise das distribuição de valores do estado de NY. Neste ponto me deparei com as questões citadas no início do documento, que me fizeram mudar minha análise para os dados de outro esttado, o Texas.
Durante as primeiras análises percebi que muitos dados necessitavam de trartamento e então resolvi preparar um script em Python para realizar alguns ajustes. Outra observação feita com inicio do trabalho, foi que a necessidade de mais dados para análise e exclusão de algumas informações desnecessárias no dataset.
DIFICULDADE COM MAPA
Referências
Abaixo o link para referências usadas para este trabalho
Detailed Files About Candidates, Parties and Other Committees - FEC
Arquivo SHP das cidades do estado do Texas - United States Census
Limites de contribuições por candidato - FEC